‘Revenge dress for a party in Sicily’: This platform is using AI to make online shopping hyper-personal

Online shopping can often feel overwhelming, especially when searching for the perfect outfit among countless options. A tech startup named Daydream is stepping in to transform this experience by allowing users to describe their desired products in everyday language. For instance, someone might request a "revenge dress for a party in Sicily this July" or "a summer bag suitable for both work and after-hours cocktails." Based in New York and San Francisco, Daydream is harnessing artificial intelligence to simplify and personalize the online shopping journey. A recent survey by Adobe Analytics, which engaged 5,000 American consumers, revealed that 39% had tried a generative AI tool for shopping in the past year, with 53% intending to do so this year. Daydream is entering a competitive market that includes tech giants like Meta, OpenAI, Amazon, and Google, all of which have developed their own AI shopping tools. Meta's AI streamlines the listing process for sellers and enhances targeted advertising, while OpenAI's shopping agent helps users purchase items across the web. Google offers a suite of AI shopping tools, including automated price tracking and virtual try-on features. However, Daydream's CEO, Julie Bornstein, believes her company has a unique advantage in the fashion sector, thanks to her extensive background in the industry. Bornstein previously served as the vice president of e-commerce at Nordstrom and held executive positions at Sephora and Stitch Fix. Her experience led her to co-found The Yes, another AI-driven shopping platform that was sold to Pinterest in 2022. "Other companies may lack the expertise and passion needed to effectively integrate AI into fashion recommendations," she explained. "Having a comprehensive catalog and the ability to connect the right products to the right customers is crucial for enhancing the shopping experience." Daydream has successfully secured $50 million in initial funding from notable investors, including Google Ventures and model Karlie Kloss. The platform functions like a virtual personal stylist, allowing users to input their requests in natural language or upload inspiration photos. Daydream then curates recommendations from over 8,000 brand partners, spanning from Uniqlo to Gucci. Users can further refine these suggestions through conversational interactions, asking for more casual or budget-friendly options. As users engage with the platform, Daydream tailors its recommendations based on individual preferences and past interactions. When users are ready to make a purchase, they are directed to the respective brand's website, with Daydream earning a commission from the sale. Unlike many other e-commerce platforms that prioritize paid advertisements, Bornstein aims for recommendations to be genuinely based on customer fit rather than financial incentives. In early tests, Daydream successfully matched user searches, such as finding a "white, fitted button-up shirt for the office without pockets," leading to an appropriate $145 option from Theory. However, the AI's recommendations aren't always spot-on; for example, a search for a "mother of the bride dress for a summer wedding in California" yielded some less formal options that might suit a bachelorette party instead. Bornstein emphasized that the company is committed to refining its AI algorithms based on user feedback. Daydream recently launched its web platform to the public, although it remains in beta testing, with plans to introduce a mobile app this fall. Looking ahead, Bornstein envisions a future where AI not only assists in shopping but also helps users coordinate new purchases with existing wardrobe items. "This concept has been in my mind for a long time, but I didn't realize how generative AI and large language models would be the key to unlocking its potential," she noted.